State-of-the-Art in Data Integrity and Privacy-Preserving in Cloud Computing

Main Article Content

Mariam Duraid Abdul-Jabbar
Yousra Abdul Alsahib S. Aldeen


Cloud computing (CC) is a fast-growing technology that offers computers, networking, and storage services that can be accessed and used over the internet. Cloud services save users money because they are pay-per-use, and they save time because they are on-demand and elastic, a unique aspect of cloud computing. However, several security issues must be addressed before users store data in the cloud. Because the user will have no direct control over the data that has been outsourced to the cloud, particularly personal and sensitive data (health, finance, military, etc.), and will not know where the data is stored, the user must ensure that the cloud stores and maintains the outsourced data appropriately. The study's primary goals are to make the cloud and data security challenges more understandable, to briefly explain the techniques used to achieve privacy and data integrity, to compare various recent studies in both pre-quantum and post-quantum, and to focus on current gaps in solving privacy and data integrity issues.

Article Details

How to Cite
“State-of-the-Art in Data Integrity and Privacy-Preserving in Cloud Computing” (2023) Journal of Engineering, 29(01), pp. 42–60. doi:10.31026/j.eng.2023.01.03.

How to Cite

“State-of-the-Art in Data Integrity and Privacy-Preserving in Cloud Computing” (2023) Journal of Engineering, 29(01), pp. 42–60. doi:10.31026/j.eng.2023.01.03.

Publication Dates


Abdulredah, S. H. and Kadhim, D. J., 2020. New Approaches of Cloud Services Access using Tonido Cloud Server for Real-Time Applications, Journal of Engineering, 26(8), p. 83–99.

Almutairi, S., Alghanmi, N., and Monowar, M. M., 2021. Survey of Centralized and Decentralized Access Control Models in Cloud Computing, International Journal of Advanced Computer Science, 12(2).

Awadallah, R., and Samsudin, A., 2021. Using blockchain in cloud computing to enhance relational database security‏, IEEE Access, Volume 9, pp. 137353-137366.

Awadallah, R., Samsudin, A., Teh, J. S., and Almazrooie, M., 2021. An integrated architecture for maintaining security in cloud computing based on blockchain‏, IEEE Access, Volume 9, pp. 69513-69526.

Banupriya, S., Kottursamy, K., and Bashir, A. K., 2021. Privacy-preserving hierarchical deterministic key generation based on a lattice of rings in public blockchain‏, Peer-to-Peer Networking and Applications, 14(5), pp. 2813-2825.

Chen, Z., Wu, A., Li, Y., Xing, Q., and Geng, S., 2021. Blockchain-enabled public key encryption with multi-keyword search in cloud computing‏, Security and Communication Networks.

Diaby, T., and Rad, B. B., 2017. Computing: a review of the concepts and deployment models‏, International Journal of Information Technology and Computer Science, 9(6), pp. 50-58.

Divya, M., and Singaravel, G., 2019. Block Chain Technology for Privacy Protection for Cloudlet-based Medical Data Sharing‏, Bonfring International Journal of Software Engineering and Soft Computing, 9(2), pp. 43-46.

El Ouazzani, Z., and El Bakkali, H., 2020. A classification of non-cryptographic anonymization techniques ensuring privacy in big data, International Journal of Communication Networks and Information Security, 12(1), pp. 142-152.

Fang, W., Wen, X. Z., Zheng, Y., and Zhou, M., 544-560. A survey of big data security and privacy preserving, IETE Technical Review, 34(5), p. 2017.


Garfinkel, S., 2015. De-identification of Personal Information‏. s.l.:US Department of Commerce, National Institute of Standards and Technology..

GDPR, 2019. General Data Protection Regulation. Art4. GDPR Definitions. [Online]

Available at: Available:

Guruprakash, J., and Koppu, S., 2020. EC-ElGamal and Genetic algorithm-based enhancement for lightweight scalable blockchain in IoT domain‏, IEEE Access, Volume 8, pp. 141269-141281.

Hemalatha, P., 2021. Monitoring and securing the healthcare data harnessing IOT and blockchain technology‏, Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12(2), pp. 2554-2561.

Hiremath, S., and Kunte, S., 2017. 2017 International Conference on Electrical, Electronics, Communication, Computer, and Optimization Techniques (ICEECCOT), pp. 306-310.

Hu, C., Li, W., Cheng, X., Yu, J., Wang, S., and Bie, R. , 2017. A secure and verifiable access control scheme for big data storage in clouds‏, IEEE Transactions on Big data, 4(3), pp. 341-355.

Huang, P., Fan, K., Yang, H., Zhang, K., Li, H., and Yang, Y., 2020. A collaborative auditing blockchain for trustworthy data integrity in cloud storage system‏, IEEE Access, Volume 8, pp. 94780-94794.

Hylock, R. H., and Zeng, X., 2019. A blockchain framework for patient-centered health records and exchange (HealthChain): evaluation and proof-of-concept study‏, Journal of medical Internet research, 21(8).

Issis, D., and Lekkas, D., 2012. Addressing cloud computing security issues, Future Generation computer systems, 28(3), pp. 583-592.

Jabbar, R., Fetais, N., Krichen, M., and Barkaoui, K., 2020. Blockchain technology for healthcare: Enhancing shared electronic health record interoperability and integrity, IEEE International Conference on Informatics, IoT, and Enabling Technologies (ICIoT), pp. pp. 310-317.

Kanwal, T., Anjum, A., and Khan, A., 2021. Privacy preservation in e-health cloud: taxonomy, privacy requirements, feasibility analysis, and opportunities.,‏Cluster Computing, 24(1), pp. 293-317.

Kokoris-Kogias, E., Alp, E. C., Gasser, L., Jovanovic, P., Syta, E., and Ford, B., 2018. Calypso: Private data management for decentralized ledgers, Cryptology ePrint Archive.

Kumar, A., and Shantala, C. P., 2020. An extensive research survey on data integrity and deduplication towards privacy in cloud storage, International Journal of Electrical and Computer Engineering, 10(2).

Lashkami, S. R., Atani, R. E., Arabnouri, A., and Salemi, G., 2020. A blockchain based framework for complete secure data outsourcing with malicious behavior prevention, 28th Iranian conference on electrical engineering (ICEE), pp. (pp. 1-7).

Lin, C. H. V., Huang, C. C. J., Yuan, Y. H., and Yuan, Z. S. S., 2020. A fully decentralized infrastructure for subscription-based IoT data trading‏, 2020 IEEE International Conference on Blockchain (Blockchain), pp. 162-169.

Liu, T., Wu, J., Li, J., Li, J., and Li, Y., 2021. Efficient decentralized access control for secure data sharing in cloud computing‏, Concurrency and Computation: Practice and Experience.

Lv, Z., Qiao, L., Hossain, M. S., and Choi, B. J., 2021. Analysis of using blockchain to protect the privacy of drone big data‏, IEEE, 35(1), pp. 44-49.

Mell, P., and Grance, T., 2011. The NIST Definition of Cloud Computing, NIST.

Mivule K., 2013. Utilizing noise addition for data privacy, an overview. arXiv, p. 1309.3958.

Mohammed, C. M., and Zeebaree, S. R., 2021. Sufficient comparison among cloud computing services: IaaS, PaaS, and SaaS: A review, International Journal of Science and Business, 5(2), pp. 17-30.

Mondal, A., Paul, S., Goswami, R. T., and Nath, S., 2020. Cloud computing security issues & challenges: A review‏, 2020 International Conference on Computer Communication and Informatics (ICCCI), January, pp. 1-5.

Qiu, L., Sun, X., and Xu, J., 2018. Categorical quantum cryptography for access control in cloud computing, Soft computing, 22(19), pp. 6363-6370.

Poornima, A., and Maheswari, D., 2020. Enhanced Ntru Public Key Crypto System Using Ear Feature Extraction, European Journal of Molecular & Clinical Medicine, 7(11).

Raban, Y., and Hauptman, A., 2018. Foresight of cyber security threat drivers and affecting technologies, Foresight.

Rajendran, K., Jayabalan, M., and Rana, M. E., 2017. A study on k-anonymity, l-diversity, and t-closeness techniques, IJCSNS, 17(12), p. 172.


Rashid, A., and Chaturvedi, A., 2019. Cloud computing characteristics and services: a brief review, International Journal of Computer Sciences and Engineering, 7(2), pp. 421-426.

Ribeiro, S. L., and Nakamura, E. T., 2019. Privacy protection with pseudonymization and anonymization in a health IoT system: results from ocariot, IEEE 19th International Conference on Bioinformatics and Bioengineering (BIBE), pp. 904-908.

Salman, T., Zolanvari, M., Erbad, A., Jain, R., and Samaka, M., 2018. Security services using blockchains: A state of the art survey‏, IEEE Communications Surveys & Tutorials, 21(1), pp. 858-880.

Shaheen, S. H., Yousaf, M., and Jalil, M., 2017. Temper proof data distribution for universal verifiability and accuracy in electoral process using blockchain, 2017 13th International Conference on Emerging Technologies (ICET), pp. 1-6, IEEE.

Shao, B., Bian, G., Wang, Y., Su, S., and Guo, C., 2018. Dynamic Data Integrity Auditing Method Supporting Privacy Protection in Vehicular Cloud Environment, IEEE Access, Volume 6, pp. 43785-43797.

Sharma, S., Gupta, G., and Laxmi, P. R., 2014. A survey on cloud security issues and techniques. arXiv:1403.5627.

Simmon, E., 2018. Evaluation of cloud computing services based on NIST SP 800-145, NIST Special Publication, 500, 322.

Singla, S., and Singh, J., 2012. Cloud data security using authentication and encryption technique‏, Global Journal of Computer Science and Technology.

Spyra, G., Buchanan, W. J., and Ekonomou, E. 2017. Sticky policies approach within cloud computing, Computers & Security, Volume 70, pp. 366-375.

Subha, T., and Jayashri, S., 2017. Efficient privacy preserving integrity checking model for cloud data storage security‏, 2016 Eighth International Conference on Advanced Computing (ICoAC), pp. 55-60, IEEE.

Sun, J., Ren, L., Wang, S., and Yao, X., 2020. A blockchain-based framework for electronic medical records sharing with fine-grained access control, Plos one, 15(10).

Tahir, M., Sardaraz, M., Muhammad, S., and Saud Khan, M., 2020. A lightweight authentication and authorization framework for blockchain-enabled IoT network in health-informatics, ‏Sustainability, 12(17).

Tang, W., Ren, J., Zhang, K., Zhang, D., Zhang, Y., and Shen, X., 2019. Efficient and privacy-preserving fog-assisted health data sharing scheme, ACM Transactions on Intelligent Systems and Technology (TIST), 10(6), pp. 1-23.

Thwin, T. T., and Vasupongayya, S., 2020. Performance Analysis of Blockchain-based Access Control Model for Personal Health Record System with Architectural Modelling and Simulation‏, Int. J. Networked Distributed Comput, 8(3), pp. 139-151.

Tong, W., Jiang, B., Xu, F., Li, Q., & Zhong, S., 2019. Privacy-preserving data integrity verification in mobile edge computing‏. 2019 IEEE 39th International Conference on Distributed Computing Systems (ICDCS) (, pp. pp. 1007-1018).

Trabelsi, S., and Sendor, J., 2021. Sticky policies for data control in the cloud‏, 2012 Tenth Annual International Conference on Privacy, Security and Trust, IEEE, pp. 75-80.

Uchibeke, U. U., Schneider, K. A., Kassani, S. H., and Deters, R., 2018. Blockchain access control ecosystem for big data security, 2018 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData), pp. pp. 1373-1378.

Xu, J., Wei, L., Wu, W., Wang, A., Zhang, Y., and Zhou, F., 2020. Privacy-preserving data integrity verification by using lightweight streaming authenticated data structures for healthcare cyber–physical system, Future Generation Computer System, Volume 108, pp. 1287-1296.

Yang, C., Tan, L., Shi, N., Xu, B., Cao, Y., and Yu, K. , 2020. AuthPrivacyChain: A blockchain-based access control framework with privacy protection in cloud‏, IEEE Access, Volume 8, pp. 70604-70615.

Yang, P., Xiong, N., and Ren, J., 2020. Data Security and Privacy Protection for Cloud Storage: A Survey, IEEE Access, Volume 8, pp. 131723-131740.

Yang, Z., Chen, Y., Huang, Y., and Li, X., 2021. Protecting personal sensitive data security in the cloud with blockchain‏, Advances in Computers, Elsevier, Volume 120, pp. 195-231.

Yousif, S. T., and Fadahl, Z. A., 2021. ProposedSecurity Framework for Mobile Data Management System, Journal of Engineering, 27(7), p. 13–23.

Yousra, S. A., , Mazleena, S., 2018. A new heuristic anonymization technique for privacy preserved datasets publication on cloud computing, Journal of Physics: Conference Series, 1003(1), p. 012030.

Zhang, J., Chen, B., Zhao, Y., Cheng, X., and Hu, F., 2018. Data security and privacy-preserving in edge computing paradigm: Survey and open issues‏, IEEE Access, Volume 6, pp. 18209-18237.

Zhang, X., Yang, L. T., Liu, C., and Chen, J., 2013. A scalable two-phase top-down specialization approach for data anonymization using MapReduce on cloud, IEEE Transactions on Parallel and Distributed Systems, 25(2), pp. 363-373.

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